CN111953783A - Data acquisition and analysis system and method for warehousing and transportation equipment - Google Patents
Data acquisition and analysis system and method for warehousing and transportation equipment Download PDFInfo
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- CN111953783A CN111953783A CN202010816589.8A CN202010816589A CN111953783A CN 111953783 A CN111953783 A CN 111953783A CN 202010816589 A CN202010816589 A CN 202010816589A CN 111953783 A CN111953783 A CN 111953783A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/06—Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
Abstract
The invention discloses a data acquisition and analysis system and a data acquisition and analysis method for warehousing and transportation equipment. The invention discloses a data acquisition and analysis system for warehousing and handling equipment, which comprises: the equipment data acquisition unit is used for acquiring the operation data of the warehousing and transportation equipment; the communication module is used for transmitting and uploading the operation data; the data processing module is used for analyzing and calculating the operation data and then storing the operation data; the data analysis module is used for processing and analyzing the data to obtain real-time operation data, an operation log, a statistical result, a diagnosis result, a prediction result and knowledge experience data of the equipment; and the application control module is used for viewing and customizing the type and range of the equipment data. The invention supports the access and operation and maintenance of various warehousing and carrying equipment, establishes the database and automatically generates the knowledge base, provides inquiry and prediction guidance for the operation and maintenance, and can be butted with other systems, thereby greatly improving the intellectualization and the applicability of the system.
Description
Technical Field
The invention relates to an intelligent warehousing technology, in particular to a data acquisition and analysis system and a data acquisition and analysis method for warehousing and handling equipment.
Background
With the continuous improvement of technical capability, the automation technology is widely applied to circulation and storage systems in various industries, and particularly, the rise of electronic commerce and rapid logistics modes in recent years drives the explosion development of the automated logistics storage market. According to statistics of the information center of the Chinese logistics technology association, the domestic automated logistics warehousing system market has grown rapidly at 23% per year in the last 16 years, and the acceleration shows a gradually accelerated trend due to the promotion of consumption upgrading and intelligent manufacturing development in the last 6 years, and the market scale of automated logistics equipment in 2022 is predicted to break through 2600 yen.
In the development of the prior art, at present, domestic automatic warehouses exceed 1000, the number of newly added automatic warehouses is continuously increased every year, most of the warehouses independently operate in an enterprise to form an automatic island, a remote operation and maintenance service means is lacked, and more of the existing operation and maintenance and service methods are tested, monitored and maintained on site by project construction parties. There is a lack of active monitoring, early warning and device lifecycle management for the devices.
Disclosure of Invention
According to an embodiment of the present invention, there is provided a data collecting and analyzing system for warehouse handling equipment, which is used for collecting and analyzing operation data of the warehouse handling equipment, and includes:
the equipment data collector is arranged on the warehousing and carrying equipment and is used for collecting the operation data of the warehousing and carrying equipment;
the communication module is used for sending and uploading the operation data;
the data processing module analyzes and calculates the operation data transmitted and uploaded by the communication module and then stores the operation data;
the data analysis module is used for processing and analyzing the data stored by the data processing module and acquiring real-time operation data, operation logs, statistical results, diagnosis results, prediction results and knowledge and experience data of the equipment;
the application control module is used for checking and customizing the data acquisition of the equipment at the control terminal, sending and uploading the data by the communication module, analyzing, calculating and storing the data by the data processing module, and processing the type and range of the analyzed data by the data analysis module.
Further, the operation data of the warehouse handling equipment collected by the equipment data collector includes but is not limited to: location, operating speed, energy consumption, mileage, task performed.
Further, the manner of sending the upload operation data by the communication module includes, but is not limited to: WIFI, a wired network, 4G and 5G access local area networks or wide area networks.
Further, the communication module transmits and uploads the operation data based on a TCP/IP protocol.
Furthermore, the data processing module comprises a real-time database and a persistent database, and the data processing module is used for storing the data after the operation data is analyzed and calculated in real time through the real-time database and storing the data in a persistent mode through the persistent database.
Furthermore, the real-time database adopts a non-relational database, the persistent database adopts a relational database, and the persistent database provides an access interface for the data analysis module.
Further, knowledge-empirical data includes, but is not limited to: the method comprises the steps of obtaining real-time and historical operation data based on single equipment and single-type equipment, and obtaining operation statistical information, operation parameter ranges, utilization rates, energy efficiency, loss and life cycles based on the single equipment and the single-type equipment in a period of time based on the real-time and historical operation data.
Further, the data analysis module generates and continuously updates a knowledge database based on knowledge experience data, and the knowledge database is used for providing basis for the data analysis module to perform diagnosis and prediction so as to obtain a statistical result, a diagnosis result and a prediction result.
According to another embodiment of the present invention, a data collecting and analyzing method for warehouse handling equipment is provided, which is used for collecting and analyzing operation data of the warehouse handling equipment, and comprises the following steps:
collecting operation data of warehousing and carrying equipment;
transmitting and uploading the operation data;
analyzing and calculating the transmitted and uploaded operation data and then storing the operation data;
processing and analyzing the stored data, and acquiring real-time operation data, operation logs, statistical results, diagnosis results, prediction results and knowledge and experience data of the equipment;
and checking and custom-defined acquisition, sending and uploading, analyzing, calculating and storing at the control terminal, and processing the type and range of the analyzed data.
Further, the operational data includes, but is not limited to, the warehouse handling equipment: running speed, energy consumption, mileage, and task execution.
Further, the way of sending the upload operation data includes, but is not limited to: WIFI, a wired network, 4G and 5G access local area networks or wide area networks.
Further, the operation data is transmitted and uploaded based on a TCP/IP protocol.
Furthermore, the data after the operation data analysis and calculation is stored in real time through a real-time database and is stored persistently through a persistent database.
Further, the real-time database adopts a non-relational database, the persistent database adopts a relational database, and the persistent database provides an access interface.
Further, knowledge-empirical data includes, but is not limited to: the method comprises the steps of obtaining real-time and historical operation data based on single equipment and single-type equipment, and obtaining operation statistical information, operation parameter ranges, utilization rates, energy efficiency, loss and life cycles based on the single equipment and the single-type equipment in a period of time based on the real-time and historical operation data.
Further, a knowledge database is generated and continuously updated based on knowledge experience data, and the knowledge database is used for providing basis for executing diagnosis and prediction so as to obtain statistical results, diagnosis results and prediction results.
According to the data acquisition and analysis system and the data acquisition and analysis method for the warehousing and transportation equipment, access and operation maintenance of various mainstream warehousing and transportation equipment are supported, the database of equipment operation and maintenance can be established, the knowledge base can be automatically generated to provide inquiry and prediction guidance for equipment maintenance and operation personnel, meanwhile, equipment data can be butted with other systems, and the intelligence and the applicability of the system are greatly improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and are intended to provide further explanation of the claimed technology.
Drawings
FIG. 1 is a system diagram of a data collection and analysis system for warehouse handling equipment according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for data collection and analysis of warehouse handling equipment according to an embodiment of the invention.
Detailed Description
The present invention will be further explained by describing preferred embodiments of the present invention in detail with reference to the accompanying drawings.
First, a data collecting and analyzing system for warehouse handling equipment according to an embodiment of the present invention will be described with reference to fig. 1, which is used for collecting and analyzing operation data of warehouse handling equipment, and the application scenario is wide.
As shown in fig. 1, the data collecting and analyzing system for warehousing and transportation equipment according to the embodiment of the present invention includes an equipment data collector 1, a communication module 2, a data processing module 3, a data analyzing module 4, and an application control module 5.
Specifically, as shown in fig. 1, the equipment data collector 1 is disposed on the warehousing and transportation equipment and is used for collecting operation data of the warehousing and transportation equipment, in this embodiment, the warehousing and transportation equipment includes but is not limited to: stacker, transfer chain, shuttle, lifting machine, quadriversal car, unpick and pile up neatly machine etc. consequently, according to the storage haulage equipment of difference, equipment data collection station 1 gathers the operational data of different grade type, for example position, functioning speed, energy consumption, mileage, the task of execution etc. the data of specific collection can be customized at control terminal through application control module 5 by the user, thereby realize the comprehensive cover to all kinds of mainstream storage haulage equipment, the suitability has been promoted greatly, can realize the comprehensive connection to each isolated warehouse and storage equipment, for 4.0 or intelligent manufacturing of industry, provide big data basis for intelligent commodity circulation.
Specifically, as shown in fig. 1, the communication module 2 is configured to transmit and upload the operation data, and the communication module 2 may transmit and upload the operation data in a manner such as WIFI, a wired network, a 4G access local area network, a 5G access local area network, or a wide area network.
Further, in this embodiment, the communication module 2 sends a message for uploading operating data based on a TCP/IP protocol.
Specifically, as shown in fig. 1, the data processing module 3 analyzes and calculates the operation data uploaded by the communication module, and stores the operation data.
Further, the data processing module 3 has a real-time database 31 and a persistent database 32, and the data processing module 3 analyzes the operation data and the interface type, and stores the calculated data in real time through the real-time database 31 and persistently through the persistent database 32.
Further, in the present embodiment, the real-time database 31 employs a non-relational database, and the real-time database 31 employs a non-relational database Redis.
Further, in this embodiment, the persistent database 32 is a relational database, and a mainstream database such as SQL Server, Oracle, MySQL is used, and provides an access interface for the data analysis module 4.
Specifically, as shown in fig. 1, the data analysis module 4 performs processing analysis on the data stored in the data processing module 3 to obtain real-time device operation data, an operation log, statistical results, diagnosis results, prediction results, and knowledge and experience data.
Further, knowledge-empirical data includes, but is not limited to: the method comprises the steps of obtaining real-time and historical operation data based on single equipment and single-type equipment, and obtaining operation statistical information, operation parameter ranges, utilization rates, energy efficiency, loss, life cycles and the like based on the single equipment and the single-type equipment in a period of time based on the real-time and historical operation data. Furthermore, the data analysis module 4 can generate and continuously update the knowledge database based on knowledge experience data, and the data analysis module 4 provides a basis for performing diagnosis and prediction through the knowledge database to obtain statistical results, diagnosis results and prediction results, so that the feedback and support of the knowledge database to the data analysis module 4 are realized, and the analysis, diagnosis and prediction capabilities and accuracy of the data analysis module 4 are continuously improved.
In this embodiment, the data analysis module 5 may provide the acquired real-time device operation data, operation log, statistical result, diagnosis result, prediction result, knowledge and experience data to the external system through an interface, and support the database intermediate table, WebService, WebApi, Socket, XML, and other modes.
Specifically, as shown in fig. 1, the application control module 5 is configured to view and customize, at the control terminal, the data acquired by the device data acquisition unit 1, send and upload the data to the communication module 2, analyze, calculate and store the data by the data processing module 3, and process the type and range of the analyzed data by the data analysis module 4. Such as the running state of the warehousing and handling equipment, log query, statistical analysis, fault alarm, overhaul prediction and the like.
Further, the types and ranges of data that application control module 5 can view and customize specifically include, but are not limited to: equipment project information maintenance, equipment types, equipment addresses, equipment parameter maintenance, equipment interface maintenance, equipment acquisition period, equipment fault maintenance, equipment state display, equipment fault statistics, equipment operation task statistics, equipment maintenance early warning and equipment maintenance application. In this embodiment, the data types and ranges that the application control module 5 can view and customize can be expanded according to actual needs.
Wherein the equipment item information maintenance comprises: project number, project type, project location, project construction time, project construction manufacturer, project amount and the like.
The device types include: the device type code, the device type name, whether the device is frozen, the time is recorded and other information.
The device address includes: the method comprises the following steps of obtaining information such as equipment number, belonged items, equipment name, equipment type, equipment physical area, equipment IP address, freezing condition and recording time.
The equipment parameter maintenance comprises the following steps: equipment number, equipment parameter name, equipment communication mode, equipment message length, message parameter type, message initial position and other information.
The equipment interface maintenance comprises: device number, interface type, interface address, whether enabled, etc.
The device acquisition cycle includes: equipment number, acquisition period, whether to enable and the like.
The equipment fault maintenance comprises the following steps: equipment type, equipment parameter name, fault type, fault processing mode, equipment maintenance mode, maintenance cycle and other information.
The device status display includes: the device number, the device type, the device parameter name, the current state value of the device, the device state description, whether the device is abnormal or not and the like.
The equipment fault statistics comprises the following steps: equipment number, equipment type, fault description, fault time and other information.
The equipment running task statistics comprises the following steps: equipment number, equipment type, running time, running task type, running task number, equipment running mileage and the like.
The equipment maintenance early warning comprises the following steps: equipment number, equipment type, equipment maintenance mode and the like.
The equipment maintenance application comprises: equipment number, equipment type, fault information, fault picture, application date, processing time and processing mode.
As described above, in the data acquisition and analysis system for warehousing handling equipment according to the embodiment of the present invention, access and operation maintenance of various types of mainstream warehousing handling equipment are supported, a database of equipment operation and maintenance can be established, a knowledge base can be automatically generated to provide query and prediction guidance for equipment maintenance and operation personnel, and meanwhile, equipment data can be docked with other systems, so that the intelligence and applicability of the system are greatly improved.
The data collection and analysis system for warehouse handling equipment according to the embodiment of the invention is described above with reference to fig. 1. Furthermore, the invention can also be applied to a data acquisition and analysis method for the warehousing and transportation equipment.
As shown in fig. 2, the data collecting and analyzing method for warehouse handling equipment according to the embodiment of the present invention is used for collecting and analyzing the operation data of the warehouse handling equipment, and includes the following steps:
in S1, collecting operation data of the warehousing and transportation equipment; wherein the operational data includes, but is not limited to, the warehouse handling equipment: the running speed, the energy consumption, the mileage, the executed tasks and the diversity of running data realize the universal application to various warehousing and carrying equipment.
In S2, the operation data is sent and uploaded; in the embodiment, the message is transmitted in a mode of accessing a local area network or a wide area network through WIFI (wireless fidelity), a wired network, 4G and 5G, the applicability is strong, and further, the operation data is transmitted and uploaded based on a TCP/IP (transmission control protocol/Internet protocol) protocol, so that the operation data can be more easily butted with various systems.
In S3, analyzing, calculating and storing the transmitted and uploaded operation data; in this embodiment, the data obtained by analyzing and calculating the operation data is stored in real time through the real-time database and is stored persistently through the persistent database. The real-time database adopts a non-relational database Redis; the persistent database adopts a relational database, such as: SQL Server, Oracle, MySQL, etc. and provides access interface.
In S4, the stored data is processed and analyzed to obtain real-time device operation data, operation logs, statistical results, diagnostic results, predictive results, and knowledge and experience data. The knowledge-experience data includes, but is not limited to: the method comprises the steps of obtaining real-time and historical operation data based on single equipment and single-type equipment, and obtaining operation statistical information, operation parameter ranges, utilization rates, energy efficiency, loss and life cycles based on the single equipment and the single-type equipment in a period of time based on the real-time and historical operation data.
Further, in the present embodiment, a knowledge database is generated and continuously updated based on knowledge-experience data, and the knowledge database is used for providing a basis for performing diagnosis and prediction to obtain statistical results, diagnosis results and prediction results. Furthermore, the data analysis module 4 can generate and continuously update the knowledge database based on knowledge experience data, and the data analysis module 4 provides a basis for performing diagnosis and prediction through the knowledge database to obtain statistical results, diagnosis results and prediction results, so that the feedback and support of the knowledge database to the data analysis module 4 are realized, and the analysis, diagnosis and prediction capabilities and accuracy of the data analysis module 4 are continuously improved.
In this embodiment, the acquired real-time device operation data, operation logs, statistical results, diagnosis results, prediction results, knowledge and experience data, and the like may be provided to an external system in an interface manner, so as to support database intermediate tables, WebService, WebApi, Socket, XML, and the like.
In S5, the control terminal views and customizes the data collection, transmission uploading, parsing, calculation, and storage, and processes the type and range of the analyzed data, in this embodiment, the data type and range that can be viewed and customized may be expanded according to actual needs, specifically including but not limited to: equipment project information maintenance, equipment types, equipment addresses, equipment parameter maintenance, equipment interface maintenance, equipment acquisition period, equipment fault maintenance, equipment state display, equipment fault statistics, equipment operation task statistics, equipment maintenance early warning and equipment maintenance application.
Wherein the equipment item information maintenance comprises: project number, project type, project location, project construction time, project construction manufacturer, project amount and the like.
The device types include: the device type code, the device type name, whether the device is frozen, the time is recorded and other information.
The device address includes: the method comprises the following steps of obtaining information such as equipment number, belonged items, equipment name, equipment type, equipment physical area, equipment IP address, freezing condition and recording time.
The equipment parameter maintenance comprises the following steps: equipment number, equipment parameter name, equipment communication mode, equipment message length, message parameter type, message initial position and other information.
The equipment interface maintenance comprises: device number, interface type, interface address, whether enabled, etc.
The device acquisition cycle includes: equipment number, acquisition period, whether to enable and the like.
The equipment fault maintenance comprises the following steps: equipment type, equipment parameter name, fault type, fault processing mode, equipment maintenance mode, maintenance cycle and other information.
The device status display includes: the device number, the device type, the device parameter name, the current state value of the device, the device state description, whether the device is abnormal or not and the like.
The equipment fault statistics comprises the following steps: equipment number, equipment type, fault description, fault time and other information.
The equipment running task statistics comprises the following steps: equipment number, equipment type, running time, running task type, running task number, equipment running mileage and the like.
The equipment maintenance early warning comprises the following steps: equipment number, equipment type, equipment maintenance mode and the like.
The equipment maintenance application comprises: equipment number, equipment type, fault information, fault picture, application date, processing time and processing mode.
The data acquisition and analysis system for the warehousing and transportation equipment and the data acquisition and analysis method for the warehousing and transportation equipment according to the embodiments of the present invention are described above with reference to fig. 1 to 2, support access and operation maintenance of various mainstream warehousing and transportation equipment, establish a database for equipment operation and maintenance, automatically generate a knowledge base, and provide query and prediction guidance for equipment maintenance and operation personnel, and meanwhile, interface the equipment data with other systems, thereby greatly improving the intelligence and applicability of the system.
It should be noted that, in the present specification, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
While the present invention has been described in detail with reference to the preferred embodiments, it should be understood that the above description should not be taken as limiting the invention. Various modifications and alterations to this invention will become apparent to those skilled in the art upon reading the foregoing description. Accordingly, the scope of the invention should be determined from the following claims.
Claims (16)
1. A data collection and analysis system for warehouse handling equipment for collecting and analyzing operational data of the warehouse handling equipment, comprising:
the equipment data collector is arranged on the warehousing and carrying equipment and is used for collecting the operation data of the warehousing and carrying equipment;
the communication module is used for sending and uploading the operation data;
the data processing module analyzes and calculates the operation data transmitted and uploaded by the communication module and then stores the operation data;
the data analysis module is used for processing and analyzing the data stored by the data processing module and acquiring real-time operation data, operation logs, statistical results, diagnosis results, prediction results and knowledge and experience data of the equipment;
the application control module is used for checking and customizing the equipment data acquisition unit at a control terminal, sending and uploading the data by the communication module, analyzing, calculating and storing the data by the data processing module, and processing the type and range of the analyzed data by the data analysis module.
2. The data collection and analysis system for warehouse handling equipment as claimed in claim 1, wherein the operational data of the warehouse handling equipment collected by the equipment data collector includes but is not limited to: location, operating speed, energy consumption, mileage, task performed.
3. The data collection and analysis system for warehouse handling equipment as claimed in claim 1, wherein the communication module sends the uploading the operational data in a manner including but not limited to: WIFI, a wired network, 4G and 5G access local area networks or wide area networks.
4. The data collection and analysis system for warehouse handling equipment as claimed in claim 3, wherein the communication module sends and uploads the operation data based on TCP/IP protocol.
5. The data collection and analysis system for warehouse handling equipment as claimed in claim 1, wherein the data processing module comprises a real-time database and a persistent database, and the data analyzed and calculated by the data processing module on the operation data is stored in real time through the real-time database and is stored persistently through the persistent database.
6. The data collection and analysis system for warehouse handling equipment as claimed in claim 5, wherein the real-time database is a non-relational database and the persistent database is a relational database, the persistent database providing an access interface for the data analysis module.
7. The data collection and analysis system for warehouse handling equipment as claimed in claim 1, wherein the empirical data includes but is not limited to: the method comprises the steps of obtaining real-time and historical operation data based on single equipment and single-type equipment, and obtaining operation statistical information, operation parameter ranges, utilization rates, energy efficiency, loss and life cycles based on the single equipment and the single-type equipment in a period of time based on the real-time and historical operation data.
8. The data collection and analysis system for warehouse handling equipment as claimed in claim 7, wherein the data analysis module generates and continuously updates a knowledge database based on the knowledge and experience data, and the knowledge database is used for providing basis for the data analysis module to perform diagnosis and prediction so as to obtain the statistical result, the diagnosis result and the prediction result.
9. A data acquisition and analysis method for warehouse handling equipment is used for acquiring and analyzing operation data of the warehouse handling equipment, and is characterized by comprising the following steps:
collecting the operation data of the warehousing and carrying equipment;
transmitting and uploading the operation data;
analyzing and calculating the transmitted and uploaded operation data and then storing the operation data;
processing and analyzing the stored data, and acquiring real-time operation data, operation logs, statistical results, diagnosis results, prediction results and knowledge and experience data of the equipment;
and checking and custom-defined acquisition, sending and uploading, analyzing, calculating and storing at the control terminal, and processing the type and range of the analyzed data.
10. The data collection and analysis method of claim 9, wherein the operational data includes but is not limited to the data of the warehouse handling equipment: running speed, energy consumption, mileage, and task execution.
11. The data collection and analysis method for warehouse handling equipment as claimed in claim 9, wherein the manner of sending and uploading the operational data includes but is not limited to: WIFI, a wired network, 4G and 5G access local area networks or wide area networks.
12. The data collection and analysis method for warehouse handling equipment as claimed in claim 11, wherein the operation data is transmitted and uploaded based on a TCP/IP protocol.
13. The data collection and analysis method for warehouse handling equipment as claimed in claim 9, wherein the analyzed and calculated data of the operation data is stored in real time through a real-time database and is stored persistently through a persistent database.
14. The data collection and analysis method for warehouse handling equipment as claimed in claim 13, wherein the real-time database is a non-relational database, the persistent database is a relational database, and the persistent database provides an access interface.
15. The data collection and analysis method of claim 9, wherein the empirical data includes but is not limited to: the method comprises the steps of obtaining real-time and historical operation data based on single equipment and single-type equipment, and obtaining operation statistical information, operation parameter ranges, utilization rates, energy efficiency, loss and life cycles based on the single equipment and the single-type equipment in a period of time based on the real-time and historical operation data.
16. The data collection and analysis method for warehouse handling equipment as claimed in claim 15, wherein a knowledge database is generated and continuously updated based on the knowledge and experience data, and the knowledge database is used for providing basis for performing diagnosis and prediction to obtain the statistical result, the diagnosis result and the prediction result.
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